Six-lncRNA Immune Prognostic Signature for Cervical Cancer

Chen, Qian and Hu, Lang and Huang, Dongping and Chen, Kaihua and Qiu, Xiaoqiang and Qiu, Bingqing (2020) Six-lncRNA Immune Prognostic Signature for Cervical Cancer. Frontiers in Genetics, 11. ISSN 1664-8021

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Abstract

Background: This study searched for immune-related long noncoding RNAs (lncRNAs) to predict the prognosis of patients with cervical cancer.

Method: We obtained immunologically relevant lncRNA expression profiles and clinical follow-up data from cervical cancer patients from The Cancer Genome Atlas database and the Molecular Signatures Database. Cervical cancer patients were randomly divided into a training group, testing group and combined group. The immune prognostic signature was constructed by Least Absolute Shrinkage and Selection Operator Cox regression, prognosis was analyzed by Kaplan–Meier curves between different groups, and the accuracy of the prognostic model was assessed by receiver operating characteristic-area under the curve (ROC-AUC) analysis.

Results: A six-lncRNA immune prognostic signature (LIPS) was constructed to predict the prognosis of cervical cancer. The six lncRNAs are as follows: AC009065.8, LINC01871, MIR210HG, GEMIN7-AS1, GAS5-AS1, and DLEU1. A ROC-AUC analysis indicated that the model could predict the prognosis of cervical cancer patients in different subgroups. A Kaplan–Meier analysis showed that patients with high risk scores had a poor prognosis; these results were equally meaningful in the subgroup analyses. Risk scores differed depending on the clinical pathology and tumor grade and were independent risk factors for cervical cancer prognosis. Gene set enrichment analysis revealed an association between the LIPS and the immune response, Wnt signaling pathway, and TGF beta signaling pathway.

Conclusion: Our study shows that the six-LIPS can predict the prognosis of cervical cancer and contribute to decisions regarding the immunotherapeutic strategy.

Item Type: Article
Subjects: STM Open Library > Medical Science
Depositing User: Unnamed user with email support@stmopenlibrary.com
Date Deposited: 04 Feb 2023 06:12
Last Modified: 24 Jun 2024 04:24
URI: http://ebooks.netkumar1.in/id/eprint/397

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